mcpbeat

TickTest — A股量化回测 MCP Server

io.github.shakagold/ticktest-mcp
local only

TickTest — A股量化回测 runs on your own machine — the client starts it, so there is no endpoint to ping. 52 installs a week from pypi.

A股量化回测 MCP Server——让 AI Agent 用自然语言回测 A 股,说一句秒出结果。单/双均线×任意周期×跨频组合,海龟交易永久免费。

Installs per day peak 153 · avg 15 · -4% w/w
a month agotoday
52
Installs / week
pypi · ticktest-mcp
Stars
on GitHub
Last commit
0 releases in 90 days
License
language unknown

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add ticktest-mcp -- uvx ticktest-mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "ticktest-mcp": {
      "args": [
        "ticktest-mcp"
      ],
      "command": "uvx"
    }
  }
}
~/.codex/config.toml
[mcp_servers.ticktest-mcp]
command = "uvx"
args = ["ticktest-mcp"]
.cursor/mcp.json
{
  "mcpServers": {
    "ticktest-mcp": {
      "args": [
        "ticktest-mcp"
      ],
      "command": "uvx"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "ticktest-mcp": {
      "args": [
        "ticktest-mcp"
      ],
      "command": "uvx"
    }
  }
}

TickTest — A股量化回测 — questions

Answers built from our own checks of this server.

Why is there no uptime for TickTest — A股量化回测?
TickTest — A股量化回测 runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package ticktest-mcp was installed 52 times last week.
How do I connect TickTest — A股量化回测?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls ticktest-mcp straight from pypi; nothing to host, nothing to sign up for.
How many people use TickTest — A股量化回测?
The pypi package ticktest-mcp was installed 52 times in the last week. Week over week that is -4%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.